BUSINESS STRATEGY

Vertica Announces Vertica 12 for Future-Proof Analytics

Vertica | June 08, 2022

Vertica
Vertica, a Micro Focus line of business, today announced the release of version 12 of the Vertica analytical database. Vertica 12 includes new major features and enhancements for analytics and machine learning across multi-cloud, hybrid on-premises and cloud, and multi-regional deployments.

The announcement was made during Vertica Unify 2022, the organization's annual user conference, where attendees learned that Vertica 12 users can now choose from the broadest range of deployment options on the market, with improved automation capabilities as well, to future-proof analytics against constantly changing technology requirements.

"While many companies are being forced to choose their analytics deployment strategy, to commit to one thing –public cloud, on-premises, or hybrid –no one knows exactly what the future may hold. "With Vertica 12, we have developed a completely flexible platform that is seamlessly hybrid. It is as capable of deploying in a SaaS model as it is on-premises. The continuous advancement of our analytical capabilities means that no matter what your future data strategies may hold, Vertica brings powerful analytics to your data."

Scott Richards, Senior Vice President and General Manager, Vertica at Micro Focus

In addition to supporting more on-premises object stores, Vertica 12 expands its Kubernetes support beyond AWS S3 to Google Cloud Storage (GCS), Azure Blob Storage and Hadoop Distributed Filesystem Storage (HDFS), making it fully cloud-native in any environment. Vertica's cloud-optimized architecture also has been enhanced with intelligent subclustering to better manage variable workloads and data sharing, helping to assign costs to owners in a logical way.

On the integration front, Vertica 12 increases the interaction with the data analytics ecosystem. Customers will benefit because key proprietary and open-source technologies work seamlessly, including a new version of VerticaPy, the Vertica Python and Jupyter Notebook interface, as well as an enhanced Spark connector and broadened PMML support.

About Vertica
The core analytical database within the Micro Focus software portfolio, Vertica is the Unified Analytics Platform, based on a massively scalable architecture with the broadest set of analytical functions spanning event and time series, pattern matching, geospatial, and end-to-end in-database machine learning. Vertica enables many customers – from Agoda to Philips to many others – to easily apply these powerful functions to the largest and most demanding analytical workloads, arming businesses and their customers with predictive business insights faster than any analytical database or data warehouse in the market.

Spotlight

The modern analyst’s relationship today is with data. Today’s most popular tools allow analysts and data scientists to play in a sandbox of data, but the explosion of data renders old tools and methodologies slow and difficult to use. In spite of this, the industry’s focus is on making those same tools perform the same operations, but faster. More powerful processors and faster memory execute queries faster, but hardware is no longer the bottleneck in data. Instead of treating big data like small data, analysts must soon begin to leverage automation to understand the patterns that define the data.


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BIG DATA MANAGEMENT

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DATA SCIENCE

KNIME Accelerates Data Science Democratization Through Snowflake Collaboration

KNIME | June 10, 2022

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BUSINESS STRATEGY

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BIG DATA MANAGEMENT

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Spotlight

The modern analyst’s relationship today is with data. Today’s most popular tools allow analysts and data scientists to play in a sandbox of data, but the explosion of data renders old tools and methodologies slow and difficult to use. In spite of this, the industry’s focus is on making those same tools perform the same operations, but faster. More powerful processors and faster memory execute queries faster, but hardware is no longer the bottleneck in data. Instead of treating big data like small data, analysts must soon begin to leverage automation to understand the patterns that define the data.

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